code: def compare_plot(predicted, real, forecast_length, model):
      plt.plot(real, linewidth=1, label="Observed", alpha=0.4)
      plt.plot(predicted, linewidth=1, label="Predicted", alpha=0.6)
      plt.legend()
      plt.xlabel("Time index")
      plt.ylabel("SSH, m")
      plt.title(
          f"Sea surface height forecast for {forecast_length} days with {model}"
      )
      plt.show()
  
imports: import os
  from copy import deepcopy
  import numpy
  import pandas
  from matplotlib import pyplot
  from sklearn.metrics import mean_squared_error, mean_absolute_error
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TsForecastingParams, TaskTypesEnum
label_desc: Use image node_id 9 for calling a global function with example usage: compare_plot(predicted, real, forecast_length, model) without return types